holoviews.plotly Package#


plotly Package#


annotation Module#

Inheritance diagram of holoviews.plotting.plotly.annotation
class holoviews.plotting.plotly.annotation.LabelPlot(element, plot=None, **params)[source]#

Bases: ScatterPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.ScatterPlot: color_index

xoffset = param.Number(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Xoffset’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2a023af0>)

Amount of offset to apply to labels along x-axis.

yoffset = param.Number(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Yoffset’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2a023640>)

Amount of offset to apply to labels along x-axis.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


callbacks Module#

Inheritance diagram of holoviews.plotting.plotly.callbacks
class holoviews.plotting.plotly.callbacks.PlotlyCallbackMetaClass(name, bases, attrs)[source]#

Bases: type

Metaclass for PlotlyCallback classes.

We want each callback class to keep track of all of the instances of the class. Using a meta class here lets us keep the logic for instance tracking in one place.

mro()#

Return a type’s method resolution order.


chart Module#

Inheritance diagram of holoviews.plotting.plotly.chart
class holoviews.plotting.plotly.chart.AreaPlot(element, plot=None, **params)[source]#

Bases: AreaMixin, ChartPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

padding = param.ClassSelector(allow_refs=False, class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2a0c8820>)

Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.BarPlot(element, plot=None, **params)[source]#

Bases: BarsMixin, ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

show_legend = param.Boolean(allow_refs=False, default=True, label=’Show legend’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f86d40>)

Whether to show legend for the plot.

multi_level = param.Boolean(allow_refs=False, default=True, label=’Multi level’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f868c0>)

Whether the Bars should be grouped into a second categorical axis level.

stacked = param.Boolean(allow_refs=False, default=False, label=’Stacked’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f84e80>)

Whether the bars should be stacked or grouped.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Make adjustments to plot extents by computing stacked bar heights, adjusting the bar baseline and forcing the x-axis to be categorical.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ChartPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.CurvePlot(element, plot=None, **params)[source]#

Bases: ChartPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

padding = param.ClassSelector(allow_refs=False, class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f86b00>)

Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

interpolation = param.ObjectSelector(allow_refs=False, default=’linear’, label=’Interpolation’, names={}, nested_refs=False, objects=[‘linear’, ‘steps-mid’, ‘steps-pre’, ‘steps-post’], rx=<param.reactive.reactive_ops object at 0x7f8f29f86a40>)

Defines how the samples of the Curve are interpolated, default is ‘linear’, other options include ‘steps-mid’, ‘steps-pre’ and ‘steps-post’.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ErrorBarsPlot(element, plot=None, **params)[source]#

Bases: ChartPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.HistogramPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ScatterPlot(element, plot=None, **params)[source]#

Bases: ChartPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

color_index = param.ClassSelector(allow_None=True, allow_refs=False, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f978e0>)

Index of the dimension from which the color will the drawn

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.SpreadPlot(element, plot=None, **params)[source]#

Bases: ChartPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

padding = param.ClassSelector(allow_refs=False, class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29f95c60>)

Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


chart3d Module#

Inheritance diagram of holoviews.plotting.plotly.chart3d
class holoviews.plotting.plotly.chart3d.Chart3DPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

projection = param.String(allow_refs=False, default=’3d’, label=’Projection’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6ba60>)

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

width = param.Integer(allow_refs=False, default=500, inclusive_bounds=(True, True), label=’Width’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6ba30>)

height = param.Integer(allow_refs=False, default=500, inclusive_bounds=(True, True), label=’Height’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6baf0>)

aspect = param.Parameter(allow_refs=False, default=’cube’, label=’Aspect’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6b9d0>)

The aspect ratio mode of the plot. By default, a plot may select its own appropriate aspect ratio but sometimes it may be necessary to force a square aspect ratio (e.g. to display the plot as an element of a grid). The modes ‘auto’ and ‘equal’ correspond to the axis modes of the same name in matplotlib, a numeric value may also be passed.

zticks = param.Parameter(allow_None=True, allow_refs=False, label=’Zticks’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6bf40>)

Ticks along z-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

camera_angle = param.NumericTuple(allow_refs=False, default=(0.2, 0.5, 0.1, 0.2), label=’Camera angle’, length=4, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6bbe0>)

camera_position = param.NumericTuple(allow_refs=False, default=(0.1, 0, -0.1), label=’Camera position’, length=3, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6bac0>)

camera_zoom = param.Integer(allow_refs=False, default=3, inclusive_bounds=(True, True), label=’Camera zoom’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29b6bc10>)

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.Path3DPlot(element, plot=None, **params)[source]#

Bases: Chart3DPlot, CurvePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.CurvePlot: padding, interpolation

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.Scatter3DPlot(element, plot=None, **params)[source]#

Bases: Chart3DPlot, ScatterPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.ScatterPlot: color_index

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.SurfacePlot(element, plot=None, **params)[source]#

Bases: Chart3DPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.TriSurfacePlot(element, plot=None, **params)[source]#

Bases: Chart3DPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


dash Module#

Inheritance diagram of holoviews.plotting.plotly.dash
class holoviews.plotting.plotly.dash.DashComponents(graphs, kdims, store, resets, children)#

Bases: tuple

children#

Alias for field number 4

count(value, /)#

Return number of occurrences of value.

graphs#

Alias for field number 0

index(value, start=0, stop=9223372036854775807, /)#

Return first index of value.

Raises ValueError if the value is not present.

kdims#

Alias for field number 1

resets#

Alias for field number 3

store#

Alias for field number 2

class holoviews.plotting.plotly.dash.HoloViewsFunctionSpec(fn, kdims, streams)#

Bases: tuple

count(value, /)#

Return number of occurrences of value.

fn#

Alias for field number 0

index(value, start=0, stop=9223372036854775807, /)#

Return first index of value.

Raises ValueError if the value is not present.

kdims#

Alias for field number 1

streams#

Alias for field number 2

class holoviews.plotting.plotly.dash.StreamCallback(input_ids, fn, output_id)#

Bases: tuple

count(value, /)#

Return number of occurrences of value.

fn#

Alias for field number 1

index(value, start=0, stop=9223372036854775807, /)#

Return first index of value.

Raises ValueError if the value is not present.

input_ids#

Alias for field number 0

output_id#

Alias for field number 2

holoviews.plotting.plotly.dash.build_derived_callback(derived_stream)[source]#

Build StreamCallback for Derived stream

Args:

derived_stream: A Derived stream

Returns:

StreamCallback

holoviews.plotting.plotly.dash.build_history_callback(history_stream)[source]#

Build StreamCallback for History stream

Args:

history_stream: A History stream

Returns:

StreamCallback

holoviews.plotting.plotly.dash.decode_store_data(store_data)[source]#

Decode a dict that was encoded by the encode_store_data function.

Args:

store_data: dict that was encoded by encode_store_data

Returns:

decoded dict

holoviews.plotting.plotly.dash.encode_store_data(store_data)[source]#

Encode store_data dict into a JSON serializable dict

This is currently done by pickling store_data and converting to a base64 encoded string. If HoloViews supports JSON serialization in the future, this method could be updated to use this approach instead

Args:

store_data: dict potentially containing HoloViews objects

Returns:

dict that can be JSON serialized

holoviews.plotting.plotly.dash.plot_to_figure(plot, reset_nclicks=0, layout_ranges=None, responsive=True, use_ranges=True)[source]#

Convert a HoloViews plotly plot to a plotly.py Figure.

Args:

plot: A HoloViews plotly plot object reset_nclicks: Number of times a reset button associated with the plot has been

clicked

Returns:

A plotly.py Figure

holoviews.plotting.plotly.dash.populate_store_with_stream_contents(store_data, streams)[source]#

Add contents of streams to the store dictionary

Args:

store_data: The store dictionary streams: List of streams whose contents should be added to the store

Returns:

None

holoviews.plotting.plotly.dash.populate_stream_callback_graph(stream_callbacks, streams)[source]#

Populate the stream_callbacks dict with StreamCallback instances associated with all of the History and Derived streams in input stream list.

Input streams to any History or Derived streams are processed recursively

Args:
stream_callbacks: dict from id(stream) to StreamCallbacks the should

be populated. Order will be a breadth-first traversal of the provided streams list, and any input streams that these depend on.

streams: List of streams to build StreamCallbacks from

Returns:

None

holoviews.plotting.plotly.dash.to_dash(app, hvobjs, reset_button=False, graph_class=<class 'dash.dcc.Graph.Graph'>, button_class=<class 'dash.html.Button.Button'>, responsive='width', use_ranges=True)[source]#

Build Dash components and callbacks from a collection of HoloViews objects

Args:

app: dash.Dash application instance hvobjs: List of HoloViews objects to build Dash components from reset_button: If True, construct a Button component that, which clicked, will

reset the interactive stream values associated with the provided HoloViews objects to their initial values. Defaults to False.

graph_class: Class to use when creating Graph components, one of dcc.Graph

(default) or ddk.Graph.

button_class: Class to use when creating reset button component.

E.g. html.Button (default) or dbc.Button

responsive: If True graphs will fill their containers width and height

responsively. If False, graphs will have a fixed size matching their HoloViews size. If “width” (default), the width is responsive but height matches the HoloViews size. If “height”, the height is responsive but the width matches the HoloViews size.

use_ranges: If True, initialize graphs with the dimension ranges specified

in the HoloViews objects. If False, allow Dash to perform its own auto-range calculations.

Returns:
DashComponents named tuple with properties:
  • graphs: List of graph components (with type matching the input

    graph_class argument) with order corresponding to the order of the input hvobjs list.

  • resets: List of reset buttons that can be used to reset figure state.

    List has length 1 if reset_button=True and is empty if reset_button=False.

  • kdims: Dict from kdim names to Dash Components that can be used to

    set the corresponding kdim value.

  • store: dcc.Store the must be included in the app layout

  • children: Single list of all components above. The order is graphs,

    kdims, resets, and then the store.

holoviews.plotting.plotly.dash.to_function_spec(hvobj)[source]#

Convert Dynamic HoloViews object into a pure function that accepts kdim values and stream contents as positional arguments.

This borrows the low-level holoviews decollate logic, but instead of returning DynamicMap with cloned streams, returns a HoloViewsFunctionSpec.

Args:

hvobj: A potentially dynamic Holoviews object

Returns:

HoloViewsFunctionSpec

holoviews.plotting.plotly.dash.update_stream_values_for_type(store_data, stream_event_data, uid_to_streams_for_type)[source]#

Update the store with values of streams for a single type

Args:

store_data: Current store dictionary stream_event_data: Potential stream data for current plotly event and

traces in figures

uid_to_streams_for_type: Mapping from trace UIDs to HoloViews streams of

a particular type

Returns:

any_change: Whether any stream value has been updated


element Module#

Inheritance diagram of holoviews.plotting.plotly.element
class holoviews.plotting.plotly.element.ColorbarPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

clim = param.NumericTuple(allow_refs=False, default=(nan, nan), label=’Clim’, length=2, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263880>)

User-specified colorbar axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

clim_percentile = param.ClassSelector(allow_refs=False, class_=(<class ‘int’>, <class ‘float’>, <class ‘bool’>), default=False, label=’Clim percentile’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263520>)

Percentile value to compute colorscale robust to outliers. If True, uses 2nd and 98th percentile; otherwise uses the specified numerical percentile value.

colorbar = param.Boolean(allow_refs=False, default=False, label=’Colorbar’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263910>)

Whether to display a colorbar.

color_levels = param.ClassSelector(allow_None=True, allow_refs=False, class_=(<class ‘int’>, <class ‘list’>), label=’Color levels’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263430>)

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

colorbar_opts = param.Dict(allow_refs=False, class_=<class ‘dict’>, default={}, label=’Colorbar opts’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263cd0>)

Allows setting including borderwidth, showexponent, nticks, outlinecolor, thickness, bgcolor, outlinewidth, bordercolor, ticklen, xpad, ypad, tickangle…

symmetric = param.Boolean(allow_refs=False, default=False, label=’Symmetric’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f29263a60>)

Whether to make the colormap symmetric around zero.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.element.ElementPlot(element, plot=None, **params)[source]#

Bases: PlotlyPlot, GenericElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

bgcolor = param.ClassSelector(allow_None=True, allow_refs=False, class_=(<class ‘str’>, <class ‘tuple’>), label=’Bgcolor’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929e590>)

If set bgcolor overrides the background color of the axis.

invert_axes = param.ObjectSelector(allow_refs=False, default=False, label=’Invert axes’, names={}, nested_refs=False, objects=[False], rx=<param.reactive.reactive_ops object at 0x7f8f2929fe80>)

Inverts the axes of the plot. Note that this parameter may not always be respected by all plots but should be respected by adjoined plots when appropriate.

invert_xaxis = param.Boolean(allow_refs=False, default=False, label=’Invert xaxis’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929dc90>)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(allow_refs=False, default=False, label=’Invert yaxis’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929fe80>)

Whether to invert the plot y-axis.

logx = param.Boolean(allow_refs=False, default=False, label=’Logx’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929e8c0>)

Whether to apply log scaling to the x-axis of the Chart.

logy = param.Boolean(allow_refs=False, default=False, label=’Logy’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929f280>)

Whether to apply log scaling to the y-axis of the Chart.

show_legend = param.Boolean(allow_refs=False, default=False, label=’Show legend’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d180>)

Whether to show legend for the plot.

xaxis = param.ObjectSelector(allow_refs=False, default=’bottom’, label=’Xaxis’, names={}, nested_refs=False, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None], rx=<param.reactive.reactive_ops object at 0x7f8f2929d780>)

Whether and where to display the xaxis, bare options allow suppressing all axis labels including ticks and xlabel. Valid options are ‘top’, ‘bottom’, ‘bare’, ‘top-bare’ and ‘bottom-bare’.

yaxis = param.ObjectSelector(allow_refs=False, default=’left’, label=’Yaxis’, names={}, nested_refs=False, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None], rx=<param.reactive.reactive_ops object at 0x7f8f2929fc40>)

Whether and where to display the yaxis, bare options allow suppressing all axis labels including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’ ‘left-bare’ and ‘right-bare’.

xticks = param.Parameter(allow_None=True, allow_refs=False, label=’Xticks’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d870>)

Ticks along x-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

yticks = param.Parameter(allow_None=True, allow_refs=False, label=’Yticks’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d600>)

Ticks along y-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

aspect = param.Parameter(allow_refs=False, default=’cube’, label=’Aspect’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d780>)

The aspect ratio mode of the plot. By default, a plot may select its own appropriate aspect ratio but sometimes it may be necessary to force a square aspect ratio (e.g. to display the plot as an element of a grid). The modes ‘auto’ and ‘equal’ correspond to the axis modes of the same name in matplotlib, a numeric value may also be passed.

invert_zaxis = param.Boolean(allow_refs=False, default=False, label=’Invert zaxis’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929fc40>)

Whether to invert the plot z-axis.

labelled = param.List(allow_refs=False, bounds=(0, None), default=[‘x’, ‘y’, ‘z’], label=’Labelled’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d1e0>)

Whether to label the ‘x’ and ‘y’ axes.

logz = param.Boolean(allow_refs=False, default=False, label=’Logz’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929ed40>)

Whether to apply log scaling to the y-axis of the Chart.

margins = param.NumericTuple(allow_refs=False, default=(50, 50, 50, 50), label=’Margins’, length=4, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d150>)

Margins in pixel values specified as a tuple of the form (left, bottom, right, top).

responsive = param.Boolean(allow_refs=False, default=False, label=’Responsive’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d810>)

Whether the plot should stretch to fill the available space.

zlabel = param.String(allow_None=True, allow_refs=False, label=’Zlabel’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929d6f0>)

An explicit override of the z-axis label, if set takes precedence over the dimension label.

zticks = param.Parameter(allow_None=True, allow_refs=False, label=’Zticks’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2929eda0>)

Ticks along z-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.element.OverlayPlot(overlay, ranges=None, batched=True, keys=None, group_counter=None, **params)[source]#

Bases: GenericOverlayPlot, ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plot.GenericOverlayPlot: show_legend, batched, legend_limit, style_grouping

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(overlay, ranges, range_type='combined', dimension=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Set the plot(s) to the given frame number. Operates by manipulating the matplotlib objects held in the self._handles dictionary.

If n is greater than the number of available frames, update using the last available frame.


images Module#

Inheritance diagram of holoviews.plotting.plotly.images
class holoviews.plotting.plotly.images.RGBPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


plot Module#

Inheritance diagram of holoviews.plotting.plotly.plot
class holoviews.plotting.plotly.plot.AdjointLayoutPlot(layout, layout_type, subplots, **params)[source]#

Bases: PlotlyPlot, GenericAdjointLayoutPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

initialize_plot(ranges=None, is_geo=False)[source]#

Plot all the views contained in the AdjointLayout Object using axes appropriate to the layout configuration. All the axes are supplied by LayoutPlot - the purpose of the call is to invoke subplots with correct options and styles and hide any empty axes as necessary.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

class holoviews.plotting.plotly.plot.GridPlot(layout, ranges=None, layout_num=1, **params)[source]#

Bases: PlotlyPlot, GenericCompositePlot

Plot a group of elements in a grid layout based on a GridSpace element object.

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

hspacing = param.Number(allow_refs=False, bounds=(0, None), default=15, inclusive_bounds=(True, True), label=’Hspacing’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f135e0>)

vspacing = param.Number(allow_refs=False, bounds=(0, None), default=15, inclusive_bounds=(True, True), label=’Vspacing’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2906b880>)

shared_axes = param.Boolean(allow_refs=False, default=True, label=’Shared axes’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f11300>)

Whether axes ranges should be shared across the layout, if disabled switches axiswise normalization option on globally.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

initialize_plot(ranges=None, is_geo=False)[source]#

Initialize the matplotlib figure.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

class holoviews.plotting.plotly.plot.LayoutPlot(layout, **params)[source]#

Bases: PlotlyPlot, GenericLayoutPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericLayoutPlot: transpose

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

hspacing = param.Number(allow_refs=False, bounds=(0, None), default=120, inclusive_bounds=(True, True), label=’Hspacing’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f124d0>)

vspacing = param.Number(allow_refs=False, bounds=(0, None), default=100, inclusive_bounds=(True, True), label=’Vspacing’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f13130>)

adjoint_spacing = param.Number(allow_refs=False, bounds=(0, None), default=20, inclusive_bounds=(True, True), label=’Adjoint spacing’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f13e50>)

shared_axes = param.Boolean(allow_refs=False, default=True, label=’Shared axes’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f12fe0>)

Whether axes ranges should be shared across the layout, if disabled switches axiswise normalization option on globally.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

initialize_plot(ranges=None, is_geo=False)[source]#

Initialize the matplotlib figure.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

class holoviews.plotting.plotly.plot.PlotlyPlot(keys=None, dimensions=None, layout_dimensions=None, uniform=True, subplot=False, adjoined=None, layout_num=0, style=None, subplots=None, dynamic=False, **params)[source]#

Bases: DimensionedPlot, CallbackPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

width = param.Integer(allow_refs=False, default=400, inclusive_bounds=(True, True), label=’Width’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f29a20>)

height = param.Integer(allow_refs=False, default=400, inclusive_bounds=(True, True), label=’Height’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28f28ac0>)

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

initialize_plot(ranges=None, is_geo=False)[source]#

Initialize the matplotlib figure.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.


raster Module#

Inheritance diagram of holoviews.plotting.plotly.raster
class holoviews.plotting.plotly.raster.HeatMapPlot(element, plot=None, **params)[source]#

Bases: HeatMapMixin, RasterPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.raster.RasterPlot: padding, nodata

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.raster.QuadMeshPlot(element, plot=None, **params)[source]#

Bases: RasterPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.raster.RasterPlot: padding

nodata = param.Integer(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Nodata’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28fe92d0>)

Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.raster.RasterPlot(element, plot=None, **params)[source]#

Bases: ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

padding = param.ClassSelector(allow_refs=False, class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0, label=’Padding’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28e5bd90>)

Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

nodata = param.Integer(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Nodata’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28e5ab30>)

Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


renderer Module#

Inheritance diagram of holoviews.plotting.plotly.renderer
class holoviews.plotting.plotly.renderer.PlotlyRenderer(*, backend, center, css, dpi, fig, fps, holomap, mode, post_render_hooks, size, widget_location, widget_mode, info_fn, key_fn, name)[source]#

Bases: Renderer

Parameters inherited from:

holoviews.plotting.renderer.Renderer: key_fn, info_fn, center, dpi, fps, mode, size, widget_location, widget_mode, css, post_render_hooks

backend = param.String(allow_refs=False, default=’plotly’, label=’Backend’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28de9a20>)

The backend name.

fig = param.ObjectSelector(allow_refs=False, default=’auto’, label=’Fig’, names={}, nested_refs=False, objects=[‘html’, ‘png’, ‘svg’, ‘auto’], rx=<param.reactive.reactive_ops object at 0x7f8f28de9c90>)

Output render format for static figures. If None, no figure rendering will occur.

holomap = param.ObjectSelector(allow_refs=False, default=’auto’, label=’Holomap’, names={}, nested_refs=False, objects=[‘scrubber’, ‘widgets’, ‘gif’, None, ‘auto’], rx=<param.reactive.reactive_ops object at 0x7f8f28de9cf0>)

Output render multi-frame (typically animated) format. If None, no multi-frame rendering will occur.

classmethod app(plot, show=False, new_window=False, websocket_origin=None, port=0)[source]#

Creates a bokeh app from a HoloViews object or plot. By default simply attaches the plot to bokeh’s curdoc and returns the Document, if show option is supplied creates an Application instance and displays it either in a browser window or inline if notebook extension has been loaded. Using the new_window option the app may be displayed in a new browser tab once the notebook extension has been loaded. A websocket origin is required when launching from an existing tornado server (such as the notebook) and it is not on the default port (‘localhost:8888’).

comm_manager[source]#

alias of CommManager

components(obj, fmt=None, comm=True, **kwargs)[source]#

Returns data and metadata dictionaries containing HTML and JS components to include render in app, notebook, or standalone document.

classmethod encode(entry)[source]#

Classmethod that applies conditional encoding based on mime-type. Given an entry as returned by __call__ return the data in the appropriate encoding.

classmethod export_widgets(obj, filename, fmt=None, template=None, json=False, json_path='', **kwargs)[source]#

Render and export object as a widget to a static HTML file. Allows supplying a custom template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’ containing the widget. Also provides options to export widget data to a json file in the supplied json_path (defaults to current path).

classmethod get_plot(obj, doc=None, renderer=None, comm=None, **kwargs)[source]#

Given a HoloViews Viewable return a corresponding plot instance.

get_plot_state(obj, doc=None, renderer=None, **kwargs)[source]#

Given a HoloViews Viewable return a corresponding figure dictionary. Allows cleaning the dictionary of any internal properties that were added

classmethod get_size(plot)[source]#

Return the display size associated with a plot before rendering to any particular format. Used to generate appropriate HTML display.

Returns a tuple of (width, height) in pixels.

html(obj, fmt=None, css=None, resources='CDN', **kwargs)[source]#

Renders plot or data structure and wraps the output in HTML. The comm argument defines whether the HTML output includes code to initialize a Comm, if the plot supplies one.

classmethod instance(**params)[source]#

Return an instance of this class, copying parameters from any existing instance provided.

classmethod load_nb(inline=True)[source]#

Loads the plotly notebook resources.

classmethod plot_options(obj, percent_size)[source]#

Given an object and a percentage size (as supplied by the %output magic) return all the appropriate plot options that would be used to instantiate a plot class for that element.

Default plot sizes at the plotting class level should be taken into account.

classmethod plotting_class(obj)[source]#

Given an object or Element class, return the suitable plotting class needed to render it with the current renderer.

classmethod save(obj, basename, fmt='auto', key=None, info=None, options=None, resources='inline', title=None, **kwargs)[source]#

Save a HoloViews object to file, either using an explicitly supplied format or to the appropriate default.

classmethod server_doc(obj, doc=None)[source]#

Get a bokeh Document with the plot attached. May supply an existing doc, otherwise bokeh.io.curdoc() is used to attach the plot to the global document instance.

classmethod state()[source]#

Context manager to handle global state for a backend, allowing Plot classes to temporarily override that state.

static_html(obj, fmt=None, template=None)[source]#

Generates a static HTML with the rendered object in the supplied format. Allows supplying a template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’.

classmethod validate(options)[source]#

Validate an options dictionary for the renderer.


selection Module#

Inheritance diagram of holoviews.plotting.plotly.selection
class holoviews.plotting.plotly.selection.PlotlyOverlaySelectionDisplay(color_prop='color', is_cmap=False, supports_region=True)[source]#

Bases: OverlaySelectionDisplay

Overlay selection display subclass for use with plotly backend


shapes Module#

Inheritance diagram of holoviews.plotting.plotly.shapes
class holoviews.plotting.plotly.shapes.BoxShapePlot(element, plot=None, **params)[source]#

Bases: GeomMixin, ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.HVLinePlot(element, plot=None, **params)[source]#

Bases: ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

apply_ranges = param.Boolean(allow_refs=False, default=False, label=’Apply ranges’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28ce6590>)

Whether to include the annotation in axis range calculations.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.HVSpanPlot(element, plot=None, **params)[source]#

Bases: ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

apply_ranges = param.Boolean(allow_refs=False, default=False, label=’Apply ranges’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28ce5ed0>)

Whether to include the annotation in axis range calculations.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.PathShapePlot(element, plot=None, **params)[source]#

Bases: ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.PathsPlot(element, plot=None, **params)[source]#

Bases: ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.SegmentShapePlot(element, plot=None, **params)[source]#

Bases: GeomMixin, ShapePlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.ShapePlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


stats Module#

Inheritance diagram of holoviews.plotting.plotly.stats
class holoviews.plotting.plotly.stats.BivariatePlot(element, plot=None, **params)[source]#

Bases: ChartPlot, ColorbarPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

filled = param.Boolean(allow_refs=False, default=False, label=’Filled’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28867610>)

ncontours = param.Integer(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Ncontours’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28867400>)

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.BoxWhiskerPlot(element, plot=None, **params)[source]#

Bases: MultiDistributionPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

boxpoints = param.ObjectSelector(allow_refs=False, default=’outliers’, label=’Boxpoints’, names={}, nested_refs=False, objects=[‘all’, ‘outliers’, ‘suspectedoutliers’, False], rx=<param.reactive.reactive_ops object at 0x7f8f28867df0>)

Which points to show, valid options are ‘all’, ‘outliers’, ‘suspectedoutliers’ and False

jitter = param.Number(allow_refs=False, default=0, inclusive_bounds=(True, True), label=’Jitter’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f28895810>)

Sets the amount of jitter in the sample points drawn. If “0”, the sample points align along the distribution axis. If “1”, the sample points are drawn in a random jitter of width equal to the width of the box(es).

mean = param.ObjectSelector(allow_refs=False, default=False, label=’Mean’, names={}, nested_refs=False, objects=[True, False, ‘sd’], rx=<param.reactive.reactive_ops object at 0x7f8f28865ff0>)

If “True”, the mean of the box(es)’ underlying distribution is drawn as a dashed line inside the box(es). If “sd” the standard deviation is also drawn.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.DistributionPlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

bandwidth = param.Number(allow_None=True, allow_refs=False, inclusive_bounds=(True, True), label=’Bandwidth’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2889de10>)

The bandwidth of the kernel for the density estimate.

cut = param.Number(allow_refs=False, default=3, inclusive_bounds=(True, True), label=’Cut’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2889e200>)

Draw the estimate to cut * bw from the extreme data points.

filled = param.Boolean(allow_refs=False, default=True, label=’Filled’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f2889fbb0>)

Whether the bivariate contours should be filled.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.MultiDistributionPlot(element, plot=None, **params)[source]#

Bases: MultiDistributionMixin, ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.ViolinPlot(element, plot=None, **params)[source]#

Bases: MultiDistributionPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

box = param.Boolean(allow_refs=False, default=True, label=’Box’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f288adbd0>)

Whether to draw a boxplot inside the violin

meanline = param.Boolean(allow_refs=False, default=False, label=’Meanline’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f288adcf0>)

If “True”, the mean of the box(es)’ underlying distribution is drawn as a dashed line inside the box(es). If “sd” the standard deviation is also drawn.

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


tabular Module#

Inheritance diagram of holoviews.plotting.plotly.tabular
class holoviews.plotting.plotly.tabular.TablePlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

width = param.Number(allow_refs=False, default=400, inclusive_bounds=(True, True), label=’Width’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f286ffaf0>)

height = param.Number(allow_refs=False, default=400, inclusive_bounds=(True, True), label=’Height’, nested_refs=False, rx=<param.reactive.reactive_ops object at 0x7f8f286ff8e0>)

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


tiles Module#

Inheritance diagram of holoviews.plotting.plotly.tiles
class holoviews.plotting.plotly.tiles.TilePlot(element, plot=None, **params)[source]#

Bases: ElementPlot

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()[source]#

Cleans up references to the plot on the attached Stream subscribers.

compute_ranges(obj, key, ranges)[source]#

Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

generate_plot(key, ranges, element=None, is_geo=False)[source]#

Override to force is_geo to True

get_aspect(xspan, yspan)[source]#

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

  • ‘data’: Just the data ranges

  • ‘extents’: Element.extents

  • ‘soft’: Dimension.soft_range values

  • ‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

  • ‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)[source]#

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)[source]#

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)[source]#

Initialize the plotly components that will represent the element

Parameters#

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns#

dict

Dictionary of the plotly components that represent the element. Keys may include:

  • ‘traces’: List of trace dicts

  • ‘annotations’: List of annotations dicts

  • ‘images’: List of image dicts

  • ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)[source]#

Initializes a new plot object with the last available frame.

Returns potential Link or Stream sources.

matches(spec)[source]#

Matches a specification against the current Plot.

push()[source]#

Pushes plot updates to the frontend.

refresh(**kwargs)[source]#

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)[source]#

Sets the root model on all subplots.

property state#

The plotting state that gets updated via the update method and used by the renderer to generate output.

traverse(fn=None, specs=None, full_breadth=True)[source]#

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)[source]#

Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None, is_geo=False)[source]#

Updates an existing plot with data corresponding to the key.


util Module#

holoviews.plotting.plotly.util.clean_internal_figure_properties(fig)[source]#

Remove all HoloViews internal properties (those with leading underscores) from the input figure.

Note: This function mutates the input figure

Parameters#

fig: dict

The figure dictionary to process.

holoviews.plotting.plotly.util.configure_matching_axes_from_dims(fig, matching_prop='_dim')[source]#

Configure matching axes for a figure

Note: This function mutates the input figure

Parameters#

fig: dict

The figure dictionary to process.

matching_prop: str

The name of the axis property that should be used to determine that two axes should be matched together. If the property is missing or None, axes will not be matched

holoviews.plotting.plotly.util.figure_grid(figures_grid, row_spacing=50, column_spacing=50, share_xaxis=False, share_yaxis=False, width=None, height=None)[source]#

Construct a figure from a 2D grid of sub-figures

Parameters#

figures_grid: list of list of (dict or None)

2D list of plotly figure dicts that will be combined in a grid to produce the resulting figure. None values maybe used to leave empty grid cells

row_spacing: float (default 50)

Vertical spacing between rows in the grid in pixels

column_spacing: float (default 50)

Horizontal spacing between columns in the grid in pixels coordinates

share_xaxis: bool (default False)

Share x-axis between sub-figures in the same column. Also link all x-axes in the figure. This will only work if each sub-figure has a single x-axis

share_yaxis: bool (default False)

Share y-axis between sub-figures in the same row. Also link all y-axes in the figure. This will only work if each subfigure has a single y-axis

width: int (default None)

Final figure width. If not specified, width is the sum of the max width of the figures in each column

height: int (default None)

Final figure width. If not specified, height is the sum of the max height of the figures in each row

Returns#

dict

A plotly figure dict

holoviews.plotting.plotly.util.get_colorscale(cmap, levels=None, cmin=None, cmax=None)[source]#

Converts a cmap spec to a plotly colorscale

Args:

cmap: A recognized colormap by name or list of colors levels: A list or integer declaring the color-levels cmin: The lower bound of the color range cmax: The upper bound of the color range

Returns:

A valid plotly colorscale

holoviews.plotting.plotly.util.merge_figure(fig, subfig)[source]#

Merge a sub-figure into a parent figure

Note: This function mutates the input fig dict, but it does not mutate the subfig dict

Parameters#

fig: dict

The plotly figure dict into which the sub figure will be merged

subfig: dict

The plotly figure dict that will be copied and then merged into fig

holoviews.plotting.plotly.util.merge_layout(obj, subobj)[source]#

Merge layout objects recursively

Note: This function mutates the input obj dict, but it does not mutate the subobj dict

Parameters#

obj: dict

dict into which the sub-figure dict will be merged

subobj: dict

dict that sill be copied and merged into obj